DBMS > Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. RDF4J vs. RRDtool vs. Sphinx

System Properties Comparison Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. RDF4J vs. RRDtool vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Search-as-a-service for web and mobile app development

Globally distributed, horizontally scalable, multi-model database service

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

RDF store

Time Series DBMS

Search engine

Secondary database models

Vector DBMS

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

azure.microsoft.com/en-us/services/search

azure.microsoft.com/services/cosmos-db

rdf4j.org

oss.oetiker.ch/rrdtool

sphinxsearch.com

Technical documentation

learn.microsoft.com/en-us/azure/search

learn.microsoft.com/azure/cosmos-db

rdf4j.org/documentation

oss.oetiker.ch/rrdtool/doc

sphinxsearch.com/docs

Developer

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Tobias Oetiker

Sphinx Technologies Inc.

Initial release

2015

2014

2004

1999

2001

Current release

1.8.0, 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V2 and FLOSS

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Implementations in Java (e.g. RRD4J) and C# available

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

HP-UX
Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

Numeric data only

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Exporting into and restoring from XML files possible

Secondary indexes

yes

All properties auto-indexed by default

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

in-process shared library
Pipes

Proprietary protocol

Supported programming languages

C#
Java
JavaScript
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Java
PHP
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

using Azure authentication

Access rights can be defined down to the item level

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